{"id":"W4288851522","doi":"10.4018/978-1-5225-8182-6.ch021","title":"Crowdsourcing the Disaster Management Cycle","year":2019,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Public Relations and Crisis Communication","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Crowdsourcing; Preparedness; Emergency management; Government (linguistics); Business; Crisis management; Public relations; Knowledge management; Political science; Computer science; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005662768,0.0004272916,0.0001990787,0.001002714,0.003011413,0.004998007,0.00101163,0.001542981,0.01795735],"category_scores_gemma":[0.001000733,0.0002354324,0.0003212037,0.001494299,0.003523094,0.003255589,0.003534123,0.001668381,0.004429421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004249977,"about_ca_system_score_gemma":0.003890567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00929267,"about_ca_topic_score_gemma":0.01218675,"domain_scores_codex":[0.9995551,0.0001248809,0.00001103638,0.00005895332,0.000191208,0.00005874012],"domain_scores_gemma":[0.9997043,0.0001402546,0.00001910294,0.00003987223,0.00005431234,0.00004212861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003490584,0.00004250356,0.0004755601,0.0005635703,0.00001027574,0.0004162221,0.01837424,0.002472625,0.001410867,0.5443271,0.1846256,0.2472465],"study_design_scores_gemma":[0.000003538114,0.000008002105,0.0003096224,0.0002352531,0.000001875677,0.0001008911,0.003350637,0.0004244041,0.0002745328,0.04888338,0.9463978,0.00001019973],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01182034,0.01146532,0.01887023,0.0125117,0.001336507,0.0002613687,0.0003480513,0.0003416625,0.9430448],"genre_scores_gemma":[0.2313563,0.02110143,0.01937625,0.003842227,0.000703176,0.0003820364,0.0006472848,0.0003443977,0.7222469],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01795735,"threshold_uncertainty_score":0.06007338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01970697023337051,"score_gpt":0.2829207931284786,"score_spread":0.2632138228951081,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}